Process analytical technology-based (PAT) model simulations of a combined cooling, seeded and antisolvent crystallization of an active pharmaceutical ingredient (API)

Trampuž, Marko; Teslić, Dušan; Likozar, Blaž

doi:10.1016/j.powtec.2020.03.027

Cited by 39 publications

(25 citation statements)

References 34 publications

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“…To achieve this, the suspension was continuously circulated through the diffractometer cell using a centrifugal pump in a loop configuration (as shown in Figure 2) at a constant flow rate of ∼0.6 L min. 1 Circulation to the diffractometer cell was started right before seed addition to record background measurements as well as in the absence of crystals. It is noted that using this online PSD measurement technique, the operating range in terms of slurry density has to be kept quite low in order to avoid multiple scattering measurement artifacts.…”

Section: Methodsmentioning

confidence: 99%

“…The evolution of the PSD during the crystallization experiments, expressed as volume fractions, was recorded in-line (every 5 min) using a laser diffractometer (Malvern Mastersizer 3000). To achieve this, the suspension was continuously circulated through the diffractometer cell using a centrifugal pump in a loop configuration (as shown in Figure ) at a constant flow rate of ∼0.6 L min …”

Section: Methodsmentioning

confidence: 99%

“…To this end, several different approaches have been employed in the past, which combine experimental design with kinetic models, most often based on population balances. 1,2 While in the majority of the models, only crystallization kinetics (growth, nucleation) are accounted for, a few studies have included the kinetics of secondary phenomena such as agglomeration and/or breakage. 3 Sodium chlorate is an inorganic salt, which is of little industrial importance but possesses a remarkable property: it crystallizes into enantiomorphous conglomerate crystals (cubic space group P2 1 3) even though it is achiral in the liquid phase.…”

Section: Introductionmentioning

confidence: 99%

“…Accessing the rates of the aforementioned mechanisms through experimental and modelling efforts is of paramount importance for any crystallization process design and development work in the pharmaceutical and (bio)chemical industries. To this end, several different approaches have been employed in the past, which combine experimental design with kinetic models, most often based on population balances. , While in the majority of the models, only crystallization kinetics (growth, nucleation) are accounted for, a few studies have included the kinetics of secondary phenomena such as agglomeration and/or breakage …”

Section: Introductionmentioning

confidence: 99%

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Crystal Growth, Dissolution, and Agglomeration Kinetics of Sodium Chlorate

Fytopoulos

Kavousanakis

Gerven

et al. 2021

Ind. Eng. Chem. Res.

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The analysis, development, and implementation of novel complex industrial crystallization processes requires kinetic knowledge of not only crystal growth and nucleation but also breakage, dissolution, and agglomeration processes. In this work, the crystal growth, dissolution, and agglomeration kinetics of sodium chlorate (NaClO3) in aqueous solutions are estimated via seeded batch experiments with in-line particle size distribution measurements. Contrary to previous works, the growth/dissolution kinetics are expressed in terms of the fundamental driving force of crystallization calculated from the activity of supersaturated solutions. The activity-based driving force is roughly 2-fold higher than the commonly used representation, which assumes ideal solutions. By fitting experimental desupersaturation data to mechanistic and empirical growth models, we show that the growth of sodium chlorate is surface integration controlled and is best described by a two-dimensional birth and spread surface nucleation mechanism. The dissolution of sodium chlorate crystals is diffusion controlled and is ∼4 times faster than the growth at an equal initial driving force. Particle agglomeration is substantial in the early stages of crystallization experiments, likely due to a strong increase in the particle number due to initial breeding secondary nucleation upon seeding. The agglomeration rate constant increases with supersaturation and decreases at higher energy dissipation rate (by increased agitation) due to a strong decrease in the efficiency of interparticle collisions. Seeding with material of different sizes does not influence the agglomeration rate constant, although substantial amount of small particles was present in all seeding materials.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Crystal Growth, Dissolution, and Agglomeration Kinetics of Sodium Chlorate

Fytopoulos

Kavousanakis

Gerven

et al. 2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…As an alternative, mechanistic modeling simulations could be used in order to obtain a more comprehensive view of crystalline systems. [58,59]…”

Section: Particle Sizementioning

confidence: 99%

Effect of Temperature and pH on Calcium Phosphate Precipitation

Vilela

Rodrigues

Fronza

et al. 2021

Crystal Research and Technology

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Calcium orthophosphates (CaP) synthesis involves several chemical equilibria that define the phases present in the final product. From the biomaterials standpoint, it is important to gain knowledge on how synthesis parameters affect phase formation and particle size. This study evaluates the interaction between temperature (24 or 45 °C) and pH conditions (4.5, 6.5, or drifting) on CaP precipitation in terms of yield, phase formation, density, morphology, and size distribution. Calcium and phosphate solutions (Ca/P = 1.0) are mixed and kept under stirring for 3 h. The precipitate is freeze-dried and characterized. Under drifting pH and pH 4.5, dicalcium phosphate dihydrate (DCPD, CaHPO 4 × 2H 2 O) is the predominant phase at both temperatures; however, some samples also present peaks ascribed to dicalcium phosphate anhydrous (DCPA, CaHPO 4 ). At pH 6.5, diffractograms reveal a mixture of low-crystallinity DCPD and DCPA (24 °C) or low crystallinity hydroxyapatite [HAP, Ca 10 (OH) 2 (PO 4 ) 6 ] (45 °C). In spite of the different morphologies (plates or aggregates), particle size remains within a relatively narrow range (D 50 = 12-28 µm). DCPD precipitation is favored under more acidic or drifting pH, while HAP is formed under nearly neutral pH 6.5.

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Recent Progress in Antisolvent Crystallization of Pharmaceuticals with a Focus on the Membrane‐Based Technologies

Haghighizadeh,

Mahdavi,

Rajabi

2024

Chem Eng & Technol

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Continuous crystallization of pharmaceuticals has been in the center of attention during the past two decades, with a more focus on the large‐scale production of active pharmaceutical ingredients. The increasing demand for pharmaceuticals requires high‐throughput production of drug crystals with different solubilities, stabilities, shapes, habits, polymorphs, and size distributions. With numerous advantages including low cost, ease of scale‐up, and superior control over polymorph and size distribution of drug crystals, antisolvent crystallization is one of the most promising crystallization methods recently attempted. However, it fails to deliver the required characteristic where the crystal systems tend to grow and for the preparation of metastable polymorphs. This review focuses on the most recent efforts to tackle these drawbacks by coupling antisolvent crystallization with cooling, supercritical‐assisted, microfluidics‐assisted, and membrane‐assisted crystallization. This systematic review aims to provide a concise summary of each coupled antisolvent technique and their positive and negative aspects. This review can be used as a guideline for pharmacist, biologists, and chemists, who are interested in the crystal engineering of pharmaceuticals to pave the way for further developments in this field.

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Process analytical technology-based (PAT) model simulations of a combined cooling, seeded and antisolvent crystallization of an active pharmaceutical ingredient (API)

Cited by 39 publications

References 34 publications

Crystal Growth, Dissolution, and Agglomeration Kinetics of Sodium Chlorate

Crystal Growth, Dissolution, and Agglomeration Kinetics of Sodium Chlorate

Effect of Temperature and pH on Calcium Phosphate Precipitation

Recent Progress in Antisolvent Crystallization of Pharmaceuticals with a Focus on the Membrane‐Based Technologies

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